Universität Bonn

Institut für Informatik

15. Mai 2024

Kolloquium: Research Talk von Prof. Dr. Ingo Scholtes Kolloquium: Research Talk von Prof. Dr. Ingo Scholtes am 23. Mai

Kolloquium: Research Talk von Prof. Dr. Ingo Scholtes
Kolloquium: Research Talk von Prof. Dr. Ingo Scholtes © Unsplash
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Wir laden herzlich zum Kolloquium von Prof. Dr. Ingo Scholtes ein!

Am 23. Mai 2024, von 12:30 bis 13:30 Uhr, wird Prof. Dr. Ingo Scholtes, Professor für Machinelles Lernen am Center for Artificial Intelligence and Data Science der Universität Würzburg sowie Assistenzprofessor (SNF) für Datenanalyse an der Universität Zürich (Schweiz), einen Research Talk (in englischer Sprache) halten.

Der Research Talk widmet sich dem Thema „The Arrow of Time in Temporal Graphs: From Laplacian Dynamics to De Bruijn Graph Neural Networks“.

Abstract:

Graph Neural Networks have become an important paradigm in the application of machine learning to data on complex systems with many interacting elements. Apart from relational data that captures which of a system's elements are connected, we increasingly have access to high-resolution time series data that captures when and in which order those connections occur. Due to the arrow of time, the temporal order of those connections shapes the causal topology of temporal graphs, i.e. which nodes can possibly causally influence each other over time. This leads to non-trivial effects that must be accounted for in the modelling of dynamical processes in graph with dynamic topologies.

Addressing this issue, I will show that the spectral properties of higher-order De Bruijn Graphs can help us to better understand how the arrow of time influences the evolution of dynamical processes in temporal graphs. Apart from improving our understanding of social, technical and biological networks with dynamic topologies, these models are the theoretical foundation for De Bruijn Graph Neural Networks, a new time-aware deep learning architecture for temporal graph data. Accounting for temporal-topological patterns in temporal graphs, our approach facilitates deep graph learning in time series data on complex networks.

Die Veranstaltung ist kostenfrei. Interessierte sind herzlich eingeladen, teilzunehmen!

Wann? Donnerstag, 23. Mai 2024, von 12:30 bis 13:30 Uhr

Wo? Institut für Informatik, Friedrich-Hirzebruch-Allee 5, 53113 Bonn, Raum 0.016

Michaela Musselmann
Institut für Informatik
Universität Bonn
Tel.: +49 228 73-4502
E-Mail: musselmann@iai.uni-bonn.de

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